DESCRIPTION: Inborn errors of metabolism are detected at birth through public newborn screening (NBS) programs using tandem mass spectrometry (MS/MS), with early and definitive diagnosis critical to patient outcomes. However, a number of obstacles contribute to the delayed diagnosis of many diseases, including high rates of false positive screening results, the inability to differentiate disease subtypes, and biochemical heterogeneity leading to discrepancies in test results. Additionally, some disorders are not included in current NBS panels. Here we propose to investigate whether the combination of genetic and metabolite technologies established in our laboratories - based on targeted next-generation sequencing (NGS) and liquid chromatography tandem mass spectrometry (LC-MS/MS) - can shorten the time to diagnosis following an abnormal NBS result, as well as facilitate detection of additional disorders. We will focus on five disorders, three that exemplify the diagnostic challenges described above (VLCADD - very long-chain acyl-CoA dehydrogenase deficiency, GA1 - glutaric acidemia type I, and MMA - methylmalonic acidemia), and two that are not currently screened (OTCD - ornithine transcarbamoylase deficiency, and CPSD - carbamoylphosphate synthetase I deficiency). These disorders are all caused by mitochondrial enzyme defects that impact the homeostasis of a variety of pathways (e.g. amino acid and organic acid metabolism). Our genetic approach of the responsible disease genes utilizes complementary long padlock probes (cLPPs) for multiplex target capture and NGS, which will identify mutations and copy-number variations (CNVs) at clinical-grade accuracy and completeness and at very low cost. The metabolite approach involves a LC-MS/MS multiplex-marker panel combining both the standard NBS panel and additional markers (e.g. small molecule intermediates of energy metabolism). This strategy is based on the finding that metabolic changes detectable on the mitochondria-systems level, which are secondary to the primary enzyme defect identified in NBS, may play a role in the expression of the disease phenotype. Accordingly, our NGS panel of 524 genes not only contains the primary disease-causing genes but also functionally related candidate genes, which we have prioritized using a gene-network analysis of mitochondrial protein-protein interaction data. We will evaluate the performance of the two technologies using whole blood samples from children with confirmed disease and their parents, as well as archived dried blood spot (DBS) specimens from the patients collected at birth and obtained from the California Newborn Screening Program. Data analysis will utilize a new family-based, statistical sequence analysis to eliminate false-negative DNA variants, individual and combined metabolic marker analysis, and a systematic patient disease-phenotype analysis. In collaboration with the California NBS program, our results will contribute to the description and implementation of novel metabolic and genetic markers for screening of inherited metabolic conditions.